Virginia Tech, Department of Civil and Environmental Engineering, Blacksburg, VA, USA.
University of North Carolina at Chapel Hill, Gillings School of Global Public Health, Department of Environmental Sciences and Engineering, Chapel Hill, NC, USA.
J Expo Sci Environ Epidemiol. 2022 May;32(3):356-365. doi: 10.1038/s41370-022-00419-8. Epub 2022 Mar 22.
Estimates of human exposure to semi-volatile organic compounds (SVOCs) such as phthalates, phthalate alternatives, and some per- and polyfluoroalkyl substances (PFAS) are required for the risk-based evaluation of chemicals. Recently, a modular mechanistic modeling framework to rapidly predict SVOC emission and partitioning in indoor environments has been presented, in which several mechanistically consistent source emission categories (SECs) were identified. However, not all SECs have well-developed emission models. In addition, data on model parameters are missing even for frequently studied SVOCs. These knowledge gaps impede the comprehensive prediction of the fate of SVOCs indoors. In this paper, sets of high-priority phthalates, phthalate alternatives, and PFAS were identified based on chemical occurrence indoors and additional selection criteria. These high-priority chemicals served as the basis for exploring model parameter availability for existing indoor SVOC emission and partitioning models. The results reveal that additional experimental and modeling work is needed to fully understand the behavior of SVOCs indoors and to predict exposures with greater confidence and lower uncertainty. Modeling approaches to fill some of the identified gaps are proposed. The prioritized sets of chemicals and proposed new modeling approaches will help guide future research. The inclusion of polar phases in the framework will further expand its applicability and scope. IMPACT STATEMENT: This paper compiles data on high-priority chemicals commonly found indoors and information on the availability of applicable models and model parameters to predict emission, partitioning, and subsequent exposure to these chemicals. Modeling approaches for a selection of the missing SECs (source emission categories) are proposed, to illustrate the path forward. The comprehensive data set helps inform researchers, exposure assessors, and policy makers to better understand the state of the science regarding modeling of indoor exposure to semi-volatile organic compounds (SVOCs) and per- and polyfluoroalkyl substances (PFAS).
需要对人类接触半挥发性有机化合物(SVOCs)进行估计,例如邻苯二甲酸酯、邻苯二甲酸酯替代品和一些全氟和多氟烷基物质(PFAS),以便对化学品进行基于风险的评估。最近,提出了一种模块化的机制模型框架,用于快速预测室内环境中的 SVOC 排放和分配,其中确定了几个机制上一致的源排放类别(SEC)。然而,并非所有 SEC 都具有完善的排放模型。此外,即使对于经常研究的 SVOC ,也缺少有关模型参数的数据。这些知识空白阻碍了室内 SVOC 命运的全面预测。在本文中,根据室内化学物质的出现和其他选择标准,确定了一组高优先级的邻苯二甲酸酯、邻苯二甲酸酯替代品和 PFAS。这些高优先级化学品为探索现有室内 SVOC 排放和分配模型的模型参数可用性提供了基础。结果表明,需要进行更多的实验和建模工作,以充分了解室内 SVOC 的行为,并以更高的置信度和更低的不确定性进行暴露预测。提出了一些建模方法来填补一些已确定的差距。优先选择的化学品集和提出的新建模方法将有助于指导未来的研究。在框架中纳入极性相将进一步扩大其适用性和范围。 影响陈述:本文汇总了常见于室内的高优先级化学品的数据,以及可用于预测这些化学品排放、分配和随后暴露的适用模型和模型参数的可用性信息。为了说明前进的道路,提出了对一些缺失 SEC(源排放类别)的选择建模方法。该综合数据集有助于为研究人员、暴露评估人员和政策制定者提供信息,使他们更好地了解有关建模室内半挥发性有机化合物(SVOC)和全氟和多氟烷基物质(PFAS)暴露的科学现状。